基于虚拟阻抗特性扰动的光伏全局最大功率跟踪控制方法

Global Maximum Power Point Tracking Method for Photovoltaic System Based on Virtual Impedance Characteristic Disturbance

当光伏阵列表面光照不均匀时,其功率特性呈现多峰特征,增加了最大功率跟踪(Maximum power point tracking,MPPT)过程的复杂性。传统MPPT方法无法跟踪到全局最大功率点(Global maximum power point,GMPP),人工智能算法虽然在一定程度上能解决多峰情况下光伏MPPT问题,但该类算法实现过程较复杂、具有一定的局限性。对适用于非均匀光照条件下的光伏全局最大功率跟踪控制策略进行研究,提出基于虚拟阻抗特性扰动(Virtual impedance characteristic disturbance,VICD)的光伏全局最大功率跟踪控制方法,将全局搜索机制引入传统扰动观察法中。当光伏阵列表面光照不均匀时,首先通过虚拟阻抗特性对光伏阵列I-U特性曲线上最大功率点所处位置区域进行初步定位,然后利用传统扰动观察法进行准确跟踪,提高了传统MPPT控制方法的适用性,应用所提控制方法能准确搜索到光伏阵列全局最大功率点,且动态性能良好。仿真与试验结果验证了所提算法的可行性与有效性。

When the surface illumination of the photovoltaic array is nonuniform,its power characteristic curve appears multi-peak phenomenon,which increases the complexity of the maximum power point tracking(MPPT)process.Traditional MPPT method cannot track the global maximum power point(GMPP).Although the artificial intelligence algorithm can solve the photovoltaic MPPT problem in the case of multiple peaks to a certain extent,the implementation process of this kind of algorithm is generally complicated and has certain limitations.In this paper,a photovoltaic global maximum power tracking control strategy for non-uniform lighting conditions is studied.Global maximum power point tracking method for photovoltaic system based on virtual load characteristic disturbance is proposed.The global search mechanism is introduced into the traditional perturbation observation method.When the illumination on the PV array surface is uneven,the location area of the maximum power point on the I-U characteristic curve of the PV array is initially located by the virtual impedance characteristics,and then the traditional perturbation observation method is used to accurately track,which improves the applicability of the traditional MPPT control method.The proposed control method can be used to accurately search the global maximum power point of the PV array,and the dynamic performance is good.Simulation and experiment results testify the feasibility and effectiveness of the proposed algorithm.